Current Newsflo's key features
Newsflo is built to identify news about individual researchers, institutes and funding agencies. Capturing media mentions enables the demonstration of your societal impact and will connect you to your scientific network on a whole new level. While Newsflo evolves over time, features will be adapted and added. At this moment Newsflo’s key features include:
- Newsflo content is powered by an algorithm using the combination of Scopus author ID and affiliation, enabling a high precision search of news surrounding an individual researcher. Currently we take all historic affiliations into account to give a full overview of media mentions linked to an author through time.
- For institutes, media mentions for individual researchers is aggregated on the affiliation level.
- News on funding agencies is identified by using the full name of the funding agency in question.
- News on academic publications is identified based on the article DOI (digital identifier), if mentioned in the news article or obtained via other websites linked to the news article.
- Clustering of similar stories from different sources is based on linguistic similarity of the full text, news article title (exact match) and publication date. In general a three day time window is used for identifying various news articles that belong to the same story.
- For some of the platforms where Newsflo integrates a 25 word summary of the full text, a snippet, is provided.
- The source rank is a LexisNexis proprietary measure of editorial prestige ranging from 1 (highest) to 5 (lowest). This is based on whether a news source has an international, regional or local focus or covers non-news sources such as blogs. This ranking is used for ordering the importance of a news source and Scival’s “Media Exposure” measurement.